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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1953 1
1955 6
1956 4
1957 2
1958 4
1959 6
1960 2
1961 1
1962 2
1963 5
1964 4
1965 1
1966 9
1967 3
1968 5
1969 2
1970 3
1971 6
1972 1
1974 4
1975 5
1976 11
1977 8
1978 8
1979 6
1980 10
1981 8
1982 13
1983 8
1984 16
1985 8
1986 13
1987 10
1988 10
1989 12
1990 13
1991 17
1992 17
1993 17
1994 22
1995 26
1996 22
1997 30
1998 31
1999 37
2000 41
2001 40
2002 43
2003 60
2004 80
2005 98
2006 142
2007 138
2008 165
2009 187
2010 181
2011 193
2012 234
2013 271
2014 298
2015 324
2016 241
2017 275
2018 273
2019 311
2020 355
2021 374
2022 435
2023 461
2024 163

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5,100 results

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Page 1
NG-DTA: Drug-target affinity prediction with n-gram molecular graphs.
Tsui LI, Hsu TC, Lin C. Tsui LI, et al. Annu Int Conf IEEE Eng Med Biol Soc. 2023 Jul;2023:1-4. doi: 10.1109/EMBC40787.2023.10339968. Annu Int Conf IEEE Eng Med Biol Soc. 2023. PMID: 38082648
Drug-target affinity (DTA) prediction is crucial to speed up drug development. The advance in deep learning allows accurate DTA prediction. However, most deep learning methods treat protein as a 1D string which is not informative to models compared to a graph repres …
Drug-target affinity (DTA) prediction is crucial to speed up drug development. The advance in deep learning allows accurate DTA …
Modality-DTA: Multimodality Fusion Strategy for Drug-Target Affinity Prediction.
Yang X, Niu Z, Liu Y, Song B, Lu W, Zeng L, Zeng X. Yang X, et al. IEEE/ACM Trans Comput Biol Bioinform. 2023 Mar-Apr;20(2):1200-1210. doi: 10.1109/TCBB.2022.3205282. Epub 2023 Apr 3. IEEE/ACM Trans Comput Biol Bioinform. 2023. PMID: 36083952
Multimodality data provide different kinds of information, with complementary roles for DTA prediction. We propose Modality-DTA, a novel deep learning method for DTA prediction that leverages the multimodality of drugs and targets. ...Experiments on three ben …
Multimodality data provide different kinds of information, with complementary roles for DTA prediction. We propose Modality-DTA …
Review of Diagnostic Test Accuracy (DTA) studies in older people.
Takwoingi Y, Quinn TJ. Takwoingi Y, et al. Age Ageing. 2018 May 1;47(3):349-355. doi: 10.1093/ageing/afy023. Age Ageing. 2018. PMID: 29528366 Review.
Diagnostic Test Accuracy (DTA) describes a field of research that aims to assess how well a test is able to detect or exclude a condition of interest. ...Some of these are generic to any DTA research and some are particularly pertinent to older adults. ...
Diagnostic Test Accuracy (DTA) describes a field of research that aims to assess how well a test is able to detect or exclude a condi …
GraphATT-DTA: Attention-Based Novel Representation of Interaction to Predict Drug-Target Binding Affinity.
Bae H, Nam H. Bae H, et al. Biomedicines. 2022 Dec 27;11(1):67. doi: 10.3390/biomedicines11010067. Biomedicines. 2022. PMID: 36672575 Free PMC article.
This work proposes GraphATT-DTA, a DTA prediction model that constructs the essential regions for determining interaction affinity between compounds and proteins, modeled with an attention mechanism for interpretability. We make the model consider the local-to-globa …
This work proposes GraphATT-DTA, a DTA prediction model that constructs the essential regions for determining interaction affi …
ELECTRA-DTA: a new compound-protein binding affinity prediction model based on the contextualized sequence encoding.
Wang J, Wen N, Wang C, Zhao L, Cheng L. Wang J, et al. J Cheminform. 2022 Mar 15;14(1):14. doi: 10.1186/s13321-022-00591-x. J Cheminform. 2022. PMID: 35292100 Free PMC article.
MOTIVATION: Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA can considerably benefit drug discovery by narrowing the search space and pruning drug-target (DT) pairs with low binding affinity scor …
MOTIVATION: Drug-target binding affinity (DTA) reflects the strength of the drug-target interaction; therefore, predicting the DTA …
SAG-DTA: Prediction of Drug-Target Affinity Using Self-Attention Graph Network.
Zhang S, Jiang M, Wang S, Wang X, Wei Z, Li Z. Zhang S, et al. Int J Mol Sci. 2021 Aug 20;22(16):8993. doi: 10.3390/ijms22168993. Int J Mol Sci. 2021. PMID: 34445696 Free PMC article.
The prediction of drug-target affinity (DTA) is a crucial step for drug screening and discovery. In this study, a new graph-based prediction model named SAG-DTA (self-attention graph drug-target affinity) was implemented. ...Results of comparative experiments on bot …
The prediction of drug-target affinity (DTA) is a crucial step for drug screening and discovery. In this study, a new graph-based pre …
NerLTR-DTA: drug-target binding affinity prediction based on neighbor relationship and learning to rank.
Ru X, Ye X, Sakurai T, Zou Q. Ru X, et al. Bioinformatics. 2022 Mar 28;38(7):1964-1971. doi: 10.1093/bioinformatics/btac048. Bioinformatics. 2022. PMID: 35134828
Experimental results on two commonly used datasets show that NerLTR-DTA outperforms some state-of-the-art competing methods. NerLTR-DTA achieves excellent performance in all application scenarios mentioned in this study, and the rm(test)2 values guarantee such excel …
Experimental results on two commonly used datasets show that NerLTR-DTA outperforms some state-of-the-art competing methods. NerLTR- …
GSAML-DTA: An interpretable drug-target binding affinity prediction model based on graph neural networks with self-attention mechanism and mutual information.
Liao J, Chen H, Wei L, Wei L. Liao J, et al. Comput Biol Med. 2022 Nov;150:106145. doi: 10.1016/j.compbiomed.2022.106145. Epub 2022 Oct 4. Comput Biol Med. 2022. PMID: 37859276
Besides, they generally combine drug and target representations directly, which may contain irrelevant-task information. In this study, we develop GSAML-DTA, an interpretable deep learning framework for DTA prediction. ...Overall, GSAML-DTA can serve as a pow …
Besides, they generally combine drug and target representations directly, which may contain irrelevant-task information. In this study, we d …
HiSIF-DTA: A Hierarchical Semantic Information Fusion Framework for Drug-Target Affinity Prediction.
Bi X, Zhang S, Ma W, Jiang H, Wei Z. Bi X, et al. IEEE J Biomed Health Inform. 2023 Nov 20;PP. doi: 10.1109/JBHI.2023.3334239. Online ahead of print. IEEE J Biomed Health Inform. 2023. PMID: 37983161
Accurately identifying drug-target affinity (DTA) plays a significant role in promoting drug discovery and has attracted increasing attention in recent years. ...However, these models capture only the low-order semantics that exist in a single protein, while the high-order …
Accurately identifying drug-target affinity (DTA) plays a significant role in promoting drug discovery and has attracted increasing a …
The DTA Mouse Model for Oligodendrocyte Ablation and CNS Demyelination.
Traka M. Traka M. Methods Mol Biol. 2019;1936:295-310. doi: 10.1007/978-1-4939-9072-6_17. Methods Mol Biol. 2019. PMID: 30820906
Therefore, the DTA mouse model is also ideal for elucidating the role of oligodendrocyte death in eliciting autoimmunity in MS. In this chapter we describe the methods we used to generate the DTA mouse model and to analyze both the primary and secondary demyelinatin …
Therefore, the DTA mouse model is also ideal for elucidating the role of oligodendrocyte death in eliciting autoimmunity in MS. In th …
5,100 results